A medical image processing apparatus can perform an image analysis process on three-dimensional images which are based on volume data including a tubular organ obtained by a medical diagnostic imaging apparatus. In particular, the medical image processing apparatus determines signal value changes caused by movements of contents (blood, lymph fluid, and contrast medium) of a tubular organ in three-dimensional images in a single time phase and estimates physical quantities (flow rate, pressure, and velocity) of the contents in the three-dimensional images in the single time phase based on the signal value changes. Then, based on the physical quantities of the contents in the three-dimensional images in the single time phase, the medical image processing apparatus can conduct analysis useful in considering diagnostic and therapeutic strategies and thereby assess severity of a lesion (stenosis or the like) in the tubular organ.
Specifically, an operator manually specifies target pixels (ROI: region of interest) in each crosscut image, which is a three-dimensional image of a coronary artery branch as a tubular organ. The medical image processing apparatus generates a coronary artery lumen feature distribution of the coronary artery branch based on pixel values (CT values) of the target pixels.
Then, based on the coronary artery lumen feature distribution, the medical image processing apparatus calculates a value of a transluminal attenuation gradient (TAG). By comparing the normal TAG value (cutoff value) of each coronary artery branch with the TAG value which is based on the coronary artery lumen feature distribution, the medical image processing apparatus can assess the severity of the lesion in the coronary artery branch from the crosscut image.
Also, by observing a displayed SPR (stretched curved planar reconstruction) image, coronary artery lumen feature distribution, CPR (curved planar reconstruction) image, and crosscut image, the operator specifies an excluded range not intend for TAG calculation along a blood flow direction (direction from an origin to a distal portion) on a coronary artery centerline in the SPR image. By setting a range corresponding to the excluded range on the abscissa (blood flow direction on the coronary artery centerline) of the coronary artery lumen feature distribution, the medical image processing apparatus can calculate the TAG value based solely on the values of the pixels in a scope other than the excluded range out of the above-mentioned target pixels.
Examples of the excluded range include a range corresponding to a very high signal range or low signal range such as a calcified area, a coronary artery bifurcation, a non-treatable distal portion, and pixel values with low reliability.
However, conventional techniques have problems in that operational burden is laid on the operator, who has to specify target pixels and excluded ranges and that calculation of TAG values takes time. Also since the target pixels and excluded ranges are specified intuitively by individual operators, there is a problem of variation with skills of the operator, making is difficult to calculate quantitative values.